Overview

A brief window of opportunity is opening. For thirty years, the
effort to create robots that can reliably and competently negotiate
novel locales on their own has been unsuccessful. In consequence, a
mass market for mobile robots other than toys has failed to
materialize. Computer power and the necessary techniques to make true
autonomous mobility possible are finally becoming available. Within a
decade they will be widespread. The first major products of this new
industry will be designed and marketed in the next several years. We
propose to undertake a venture towards that end, building on our
thirty years of foundational experience. An attractive form for the
venture is a licensing company, to develop the technology and market
it to end manufacturers.

Since 1992 weve developed programs to process data from robot
sensors, especially stereoscopic cameras, into dense three-dimensional
maps of the surroundings. These would form the core of the venture,
but there remains a long list of additional issues and ideas to be
explored, among them improved preliminary processing of images,
automatic optimization, route planning, robot localization within
maps, object classification and many applications-specific topics.
These might be addressed in early in commercial work, but are also
suitable for university research, as now. From the research point of
view, a modest investment in this direction could have a
disproportionate payback, by sparking vigorous, self-sustaining
growth. A lively industry would be fertile soil for promising
robotics research that today is often lost for lack of a sustaining
context. There are many precedents in the computer industry.
Computers, integrated circuits and the internet, once research
initiatives, now grow vigorously in the open market. We judge
robotics to be on the verge of an analogous flowering. Keeping the
work in an open research setting as long as possible would maximize
its availability to others.

The concept of using self-guiding mobile robots for transport,
cleaning, and inspection has existed for most of the twentieth
century, but has been realized in only modest ways. A few tens of
thousands of AGVs (Automatically Guided Vehicles) are at work in
factories, warehouses and other institutional locations. Many are
guided by buried signal-emitting wires defining their routes, with
switches signaling endpoints and collisions, a technique developed in
the 1960s. More advanced models, made possible by the advent of
microprocessors in the 1980s, use more flexible cues, such a optical
markings on a tiled floor. The latter may use ultrasonics and
infrared proximity sensors to detect and possibly negotiate their way
around obstacles. The most advanced machines, manufactured in the
late 1980s and 1990s, are guided by navigational markers, such as
retroreflective targets at strategic locations, and by specialized
site-specific programming exploiting existing features, like
walls.

The newer systems can be installed with less physical effort, but all
require the services of a specialist to program the initial setup, and
for layout and route changes. The expense, inconvenience,
inflexibility and lack of independence stemming from the elaborate
setup greatly reduces the potential market for these systems. Only
very stable and high-value routes are candidates, and the high cost
reduces any economic advantage over human guided vehicles. Fully
autonomous robots, which could be simply shown or led through their
paces by nonspecialists, then trusted to execute their tasks reliably,
would have a far greater market.

A generation of fully autonomous mobile robots, which navigate
without route preparation, has emerged in research laboratories
worldwide in the 1990s, made possible by more powerful
microprocessors. The majority of these use sonar or laser
rangefinders to build coarse two-dimensional maps of their
surroundings, from which they locate themselves relative to their
surroundings, and plan paths between destinations. The limited
information in horizontal maps allows for certain ambiguities, and
when navigating in new areas, these machines have a mean time between
difficulties (getting lost, stuck, or even falling) measured in hours.
Previous generations of commercial robots were not accepted by
customers until the between failure time exceeded several months. It
appears unlikely that two-dimensional autonomous navigation can meet
this standard.

Our own research mobile robot research , ongoing since the 1970s, has
investigated sparse three-dimensional models and dense two-dimensional
maps, using camera, sonar and laser sensors. In the last five years,
taking advantage of the most powerful microprocessors, we have
developed efficient programs that maintain three-dimensional
volumetric maps of a robots surroundings, containing about a
thousand times the information of two-dimensional maps. Our main
sensors have been inexpensive video cameras. We judge that this
technique is more than adequate to be the core of a commercially
viable autonomous mobile robot navigator, the first in our thirty
years of work. As a bonus, the three dimensional maps produced can be
used in the robot to recognize doors and furniture-sized objects in
the surroundings. We have demonstrated the core techniques, but
several person-years of research and development are still needed to
produce even a complete laboratory prototype. This is a good time to
start a focused effort, as sufficiently powerful research computers
are just becoming available. With 1,000 MIPS (millions of
instructions per second), which should be available in high-end
personal computers in 1998, our programs can digest a glimpse of the
world in less than a second, which should be adequate for slow speed
indoor robots. The same 1,000 MIPS should be available in compact low
cost microcontrollers, suitable for use in even small robots, before
2005.

A projected first commercial product from this effort is a
basketball-sized navigation head to be retrofitted on
existing robots, providing them with full autonomy. It would contain
360 degrees of stereoscopic cameras and other sensors, an inexpensive
inertial navigation system to inform it about small motions without
depending on accurate odometry from robot wheels, 1,000 MIPS of
computational power, software for basic navigation, and software hooks
for applications specific programming and hardware interfaces for
vehicle controls. Offered as an OEM product to existing AGV
manufacturers and others, it could quite possibly expand the market
for AGVs tenfold from the current tens of thousands.

A possible first product with mass-market potential is a small robot vacuum cleaner, which can reliably and systematically keep clean designated rooms in a home following a simple introduction to the location.

The simple vacuum cleaner may be followed by larger and smarter utility robots with dusting arms. In subsequent products, arms may become stronger and more sensitive, to clean other surfaces. Mobile robots with dexterous arms, vision and touch sensors will be be able to do various tasks. With proper programming and minor accessories, such machines could pick up clutter, retrieve and deliver articles, take inventory, guard homes, open doors, mow lawns or play games. New applications will expand the market and spur further advancements, when existing robots fall short in acuity, precision, strength, reach, dexterity or processing power. Capability, numbers sold, engineering and manufacturing quality, and cost effectiveness should increase in a mutually reinforcing spiral. Ultimately the process could result in universal robots which can be do many different tasks, orchestrated by applications-specific programs.